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Poitras, Eric; Butcher, Kirsten R.; Orr, Matthew; Hudson, Michelle A.; Larson, Madlyn – Interactive Learning Environments, 2022
This study mined student interactions with visual representations as a means to automate assessment of learning in a complex, inquiry-based learning environment. Log trace data of 143 middle school students' interactions with an interactive map in Research Quest (an inquiry-based, online learning environment) were analyzed. Students used the…
Descriptors: Middle School Students, Electronic Learning, Maps, Science Instruction
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Cenka, Baginda Anggun Nan; Santoso, Harry B.; Junus, Kasiyah – Knowledge Management & E-Learning, 2022
Online learning implementation has been growing year by year across countries, including Indonesia. Many higher education institutions use a Learning Management System (LMS) to facilitate online learning. Unfortunately, many issues arise during online learning implementation, such as a lack of student behaviour monitoring. This study adopts an…
Descriptors: Knowledge Management, Electronic Learning, Integrated Learning Systems, Student Behavior
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Wakelam, Edward; Jefferies, Amanda; Davey, Neil; Sun, Yi – British Journal of Educational Technology, 2020
The measurement of student performance during their progress through university study provides academic leadership with critical information on each student's likelihood of success. Academics have traditionally used their interactions with individual students through class activities and interim assessments to identify those "at risk" of…
Descriptors: Academic Achievement, At Risk Students, Data Analysis, Identification
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Godwin-Jones, Robert – Language Learning & Technology, 2021
Data collection and analysis is nothing new in computer-assisted language learning, but with the phenomenon of massive sets of human language collected into corpora, and especially integrated into systems driven by artificial intelligence, new opportunities have arisen for language teaching and learning. We are now seeing powerful artificial…
Descriptors: Data Collection, Academic Achievement, Learning Analytics, Computer Assisted Instruction
Michelle R. Waters – ProQuest LLC, 2021
Credit recovery in public education has become an intervention used widely in the United States to address the rising number of students who are not meeting with success in the completion of required courses in the traditional education setting. With the passing of the Every Student Succeeds Act in 2015, public schools sought a method to motivate…
Descriptors: Repetition, Required Courses, Educational Legislation, Elementary Secondary Education
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Leblay, Joffrey; Rabah, Mourad; Champagnat, Ronan; Nowakowski, Samuel – International Association for Development of the Information Society, 2018
How can we learn to use properly business software, digital environments, games or intelligent tutoring systems (ITS)? Mainly, we assume that the new user will learn by doing. But what about the efficiency of such a method? Our approach proposes an answer by introducing on-line coaching. In learning process, learners may need guidance to help them…
Descriptors: Intelligent Tutoring Systems, Coaching (Performance), Efficiency, Learning Processes
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Mangaroska, Katerina; Giannakos, Michail – IEEE Transactions on Learning Technologies, 2019
As the fields of learning analytics and learning design mature, the convergence and synergies between the two are becoming an important area for research. This paper intends to summarize the main outcomes of a systematic review of empirical evidence on learning analytics for learning design. Moreover, this paper presents an overview of what and…
Descriptors: Data Analysis, Instructional Design, Learning Activities, Databases
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Qazdar, Aimad; Er-Raha, Brahim; Cherkaoui, Chihab; Mammass, Driss – Education and Information Technologies, 2019
The use of machine learning with educational data mining (EDM) to predict learner performance has always been an important research area. Predicting academic results is one of the solutions that aims to monitor the progress of students and anticipates students at risk of failing the academic pathways. In this paper, we present a framework for…
Descriptors: Data Analysis, Academic Achievement, At Risk Students, High School Students
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Pardo, Abelardo; Han, Feifei; Ellis, Robert A. – IEEE Transactions on Learning Technologies, 2017
Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…
Descriptors: Student Centered Learning, Learning Theories, College Students, Academic Achievement
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Aguilar, Jose; Cordero, Jorge; Buendía, Omar – Journal of Educational Computing Research, 2018
In this article, we propose the concept of "Autonomic Cycle Of Learning Analysis Tasks" (ACOLAT), which defines a set of tasks of learning analysis, whose objective is to improve the learning process. The data analysis has become a fundamental area for the knowledge discovery from data extracted from different sources. In the autonomic…
Descriptors: Data Analysis, Learning Processes, Decision Making, Instructional Improvement
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Reilly, Joseph M.; Schneider, Bertrand – International Educational Data Mining Society, 2019
Collaborative problem solving in computer-supported environments is of critical importance to the modern workforce. Coworkers or collaborators must be able to co-create and navigate a shared problem space using discourse and non-verbal cues. Analyzing this discourse can give insights into how consensus is reached and can estimate the depth of…
Descriptors: Problem Solving, Discourse Analysis, Cooperative Learning, Computer Assisted Instruction
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Akhtar, S.; Warburton, S.; Xu, W. – International Journal of Technology and Design Education, 2017
In this paper we report on the use of a purpose built Computer Support Collaborative learning environment designed to support lab-based CAD teaching through the monitoring of student participation and identified predictors of success. This was carried out by analysing data from the interactive learning system and correlating student behaviour with…
Descriptors: Foreign Countries, Undergraduate Students, Electronic Learning, Computer Assisted Instruction
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Demir, Seda; Basol, Gülsah – Educational Sciences: Theory and Practice, 2014
The aim of the current study is to determine the overall effects of Computer-Assisted Mathematics Education (CAME) on academic achievement. After an extensive review of the literature, studies using Turkish samples and observing the effects of Computer-Assisted Education (CAE) on mathematics achievement were examined. As a result of this…
Descriptors: Mathematics Education, Computer Assisted Instruction, Academic Achievement, Meta Analysis
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Burns, Matthew K.; Klingbeil, David A.; Ysseldyke, Jim – Psychology in the Schools, 2010
Technology-enhanced formative evaluation (TEFE) could enhance student achievement while diminishing the burden of formative evaluation for educators. The current study examined data from 360 randomly selected schools that either used a TEFE program for 1 year to 4 years 11 months, for 5 or more years, or not at all. Analyses of covariance found a…
Descriptors: Formative Evaluation, Mathematics Tests, Accountability, White Students
Gemin, Butch; Pape, Larry; Vashaw, Lauren; Watson, John – Evergreen Education Group, 2015
Online learning has steadily become a more integral strategy for schools and districts in their efforts to offer students greater access to the courses they need. Where in the past, much of the online learning activity happened at the state level or regional level, more and more schools are exercising greater control over their online and digital…
Descriptors: Elementary Secondary Education, Electronic Learning, Educational Policy, Educational Practices
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